9.
HardwareMembase:● RAM, RAM, RAM!● Fast disk (throughput) helpful for write- intensive applications, and disk-heavy ops (rebalance)● Network bandwidth may become an issue● Adding more nodes can help with all three

10.
Hardware—RAMProper cluster sizing is #1● Couchbase.org wiki: Sizing Guidelines● Main variables include total number of items, size of working set, replicas and per-item overhead● Under-provisioning reduces elasticity

11.
Hardware—DiskFast disk not too important…until it is● Rebalance can move a lot of data around● Especially when disk > RAM● Warm-up time after node restart● Under-provisioning reduces elasticity● More nodes spread out the I/O● SSD, RAID, the usual stuf

13.
Hardware—CloudCloud hosting brings variability● Disk bandwidth can occasionally drop● Even identical instances may perform diferently● Large instances more reliable● More instances provide redundancy● Best bang-for-the-buck still an open question

20.
Modeling—Doc SizeBreak up serial items to separate docs● E.g., comments, events, other “feeds”● Each entry is self-described● Avoids write contention on a container● Avoid read/write of container contents just to make a small addition● May be gathered with map/reduce view

21.
Modeling—Key SizeUse short key values● At the clustering layer, all keys are kept in RAM, tracked for replicas, etc.● 255 bytes max length, but prefer short keys● At CouchDB layer, id is likewise used in many places, and short ids are more efficient● Semantic keys